LinkedIn Announces New, Privacy-Friendly Approaches to Data Collection and Ad Targeting
A new article on Social Media Today reports that amid the evolving data privacy landscape, and significant changes to how apps can collect data as a result of regulatory shifts and operating system updates, social platforms are working to establish new data collection processes, in order to ensure that marketers can still reach their target audiences, without using previously available insights.
LinkedIn's looking to address this with the implementation of various new processes, including a new 'Group Identity' targeting option, which will utilize its own first-party data, as entered on user profiles, to categorize audiences into more segments.
In essence, the process enables you to use LinkedIn categorization to reach users with your promotions on third-party sites that are part of LinkedIn's Audience network. You've always been able to use the same type of targeting on LinkedIn itself, but this new process will provide more options for reaching audience segments based on more qualifiers, without you needing to specify your audiences through your own targeting selections. The actual benefits of this will vary, but it could be a good way to reach, say, 'IT managers' across the web with promotions based on their LinkedIn profile information.
In addition to this, LinkedIn's also testing new machine learning models which will estimate and report campaign conversations across channels "with a high degree of accuracy by using data from across our platform". Conversion tracking has been made much more difficult by Apple's ATT update, but LinkedIn's hoping that it can create more accurate conversion modeling processes in order to continue to provide this type of tracking insight.
LinkedIn's also working on the attribution of offline or offsite conversion events to LinkedIn campaigns. The accuracy of these will likely be variable, but the hope is that through advanced techniques, social platforms will still be able to provide valuable and actionable insight for campaigns, in order to help marketers maximize their results.
LinkedIn's looking to address this with the implementation of various new processes, including a new 'Group Identity' targeting option, which will utilize its own first-party data, as entered on user profiles, to categorize audiences into more segments.
| "With Group Identity for B2B, we leverage our first-party data to group members together based on shared professional identity attributes, such as seniority and industry. This process helps you reach your intended audiences across channels, like the LinkedIn Audience Network, without the need for individual-level tracking across sites." |
In addition to this, LinkedIn's also testing new machine learning models which will estimate and report campaign conversations across channels "with a high degree of accuracy by using data from across our platform". Conversion tracking has been made much more difficult by Apple's ATT update, but LinkedIn's hoping that it can create more accurate conversion modeling processes in order to continue to provide this type of tracking insight.
LinkedIn's also working on the attribution of offline or offsite conversion events to LinkedIn campaigns. The accuracy of these will likely be variable, but the hope is that through advanced techniques, social platforms will still be able to provide valuable and actionable insight for campaigns, in order to help marketers maximize their results.
